{"id":"W7061182063","doi":"","title":"Parallel finite element processing using Gaussian belief propagation inference on probabilistic graphical models","year":2015,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Superconducting and THz Device Technology","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Belief propagation; Graphical model; Finite element method; Inference; Scalability; Probabilistic logic; Approximate inference; Robustness (evolution); Variable elimination","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013522,0.0008097019,0.001121772,0.0008633486,0.0005698717,0.001091567,0.001758106,0.00134658,0.002605552],"category_scores_gemma":[0.005127561,0.0007658012,0.001245773,0.001088538,0.001042826,0.0012499,0.001518599,0.001914584,0.0007076562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008753439,"about_ca_system_score_gemma":0.001358983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009385702,"about_ca_topic_score_gemma":0.0108249,"domain_scores_codex":[0.9990839,0.0002593233,0.00004237719,0.0001898931,0.0003445036,0.00007995223],"domain_scores_gemma":[0.9979665,0.001254342,0.0001549157,0.0001997207,0.0003423906,0.00008213229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006744577,0.00002888822,0.0004017403,0.00005426764,0.00004079759,0.0000564838,0.00008411632,0.9171918,0.002295899,0.01673578,0.00113655,0.06190614],"study_design_scores_gemma":[0.000003071588,0.000003244228,0.00002114244,0.000001897407,0.000001934867,0.000004568681,0.000003262652,0.9943453,0.0002779846,0.00508072,0.0002545145,0.000002476456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002508981,0.00005653027,0.9964451,0.00007773186,0.00001389723,0.00001205882,0.00002721542,0.0003687829,0.0004897186],"genre_scores_gemma":[0.2568512,0.00026826,0.7388608,0.0002193814,0.00007982957,0.000162288,0.0003853343,0.0002955043,0.002877286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009385702,"threshold_uncertainty_score":0.01866215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04274208410883736,"score_gpt":0.2907368348850105,"score_spread":0.2479947507761731,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}